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AI Podcasts

January 5, 2026

Welcome to AIE CODE - Jed Borovik, Google DeepMind

AI Engineer

AI
Key Takeaways:
  1. The transition from general-purpose LLMs to specialized coding agents that operate on the entire codebase rather than isolated snippets.
  2. Audit your current stack for agentic readiness. Prioritize tools that integrate with Gemini 3 or similar high-reasoning models to automate repetitive pull requests.
  3. Code is the substrate of the digital world. If you control the means of AI code generation, you control the speed of innovation for every other industry.
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January 5, 2026

Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic

AI Engineer

AI
Key Takeaways:
  1. The industry is moving from "Chat-as-Interface" to "Computer-as-Interface" where models operate directly on file systems.
  2. Replace your complex list of fifty tools with a single Bash tool and a secure sandbox.
  3. The winners in the agent race will not build the best prompts. They will build the best infrastructure for models to execute code.
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December 31, 2025

Infinity, Paradoxes, Gödel Incompleteness & the Mathematical Multiverse | Lex Fridman Podcast #488

Lex Fridman

AI
Key Takeaways:
  1. The move from a singular "Universe" view to a "Multiverse" perspective mirrors the transition from centralized monoliths to fragmented, interoperable ecosystems.
  2. Build systems that fail gracefully when hitting Gödelian limits.
  3. Truth is a vast ocean while proof is a small boat. Your roadmap must account for the reality that your system will eventually encounter truths it cannot verify.
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December 31, 2025

AI in 2026: 3 Predictions For What’s To Come (a16z Big Ideas)

a16z

AI
Key Takeaways:
  1. The Macro Pivot: Outcome-Based Intelligence. We are moving from AI as a Service to Results as a Service where software value is tied to revenue generation rather than seat licenses.
  2. The Tactical Edge: Verticalize the Data. Build in sectors with non-public outcome data to create a compounding moat that resists commoditization by foundation models.
  3. The winners of 2026 will be those who use AI to solve core human needs for connection and discovery while building defensible, data-rich business models.
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December 31, 2025

AutoGrad Changed Everything (Not Transformers) [Dr. Jeff Beck]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The Macro Transition: Moving from "Big Model" monoliths to "Lots of Little Models" where distributed Bayesian assets represent specific physical objects.
  2. The Tactical Edge: Prioritize "Object-Centered" architectures that track uncertainty. This allows robots to "phone a friend" when encountering novel data.
  3. The LLM era is hitting a wall of implicit representation. The next 12 months belong to those building explicit, causal world models grounded in physics rather than language.
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December 31, 2025

[State of Post-Training] From GPT-4.1 to 5.1: RLVR, Agent & Token Efficiency — Josh McGrath, OpenAI

Latent Space

AI
Key Takeaways:
  1. The move from "bigger is better" to "smarter is cheaper" as token efficiency becomes the primary metric for agentic success.
  2. Prioritize building on models that demonstrate high performance on "graph walk" evals to ensure your long-context applications actually work.
  3. Utilitarian and efficient models that prioritize task completion over cheery personality will dominate the developer market.
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December 31, 2025

[State of Evals] LMArena's $100M Vision — Anastasios Angelopoulos, LMArena

Latent Space

AI
Key Takeaways:
  1. The Macro Trend: The transition from static benchmarks to live human-in-the-loop evaluation. As models saturate fixed tests, the only remaining signal is subjective human preference at scale.
  2. The Tactical Edge: Monitor secret model drops on Arena to spot frontier capabilities before official releases. This provides a lead time advantage for builders choosing their tech stack.
  3. The Bottom Line: Arena is the new kingmaker. If you are building AI products, their expert-tier data is the most reliable map for navigating the frontier.
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December 31, 2025

[State of Context Engineering] Agentic RAG, Context Rot, MCP, Subagents — Nina Lopatina, Contextual

Latent Space

AI
Key Takeaways:
  1. The move from small models to medium models (15B to 70B) suggests that reasoning capability is outstripping the desire for low-latency edge deployment.
  2. Implement instruction-following re-rankers to prune your context window. This prevents the model from getting confused by irrelevant data.
  3. Stop building toys. The next year belongs to those who can build full agentic systems that handle billions of tokens without losing the plot.
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December 31, 2025

[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton

Latent Space

AI
Key Takeaways:
  1. The wall between RL and self-supervised learning is crumbling, leading to a unified "representation-first" approach to AI.
  2. Swap your reward-heavy objectives for contrastive representation learning to access deeper, more stable architectures.
  3. If you aren't planning for RL models with 100x the current depth, you're building for the past.
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Crypto Podcasts

January 29, 2026

The Most Underrated Chain: Celo’s Surprising Traction Around the World

Bankless

Crypto
Key Takeaways:
  1. The migration of the $3.2 quadrillion FX market to transparent, 24/7 blockchain rails.
  2. Build consumer-facing apps that utilize the phone-number-as-identity standard to capture the next 100 million users.
  3. Celo is the leading laboratory for real-world crypto adoption, proving that the Global Venmo dream is finally scaling.
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January 29, 2026

What If DOGE Actually Becomes Real Money?

The DCo Podcast

Crypto
Key Takeaways:
  1. The transition from speculative assets to utility-based currencies.
  2. Integrate low-fee payment rails like the Dogecoin GigaWallet to capture micro-transaction volume.
  3. Dogecoin is the dark horse of the next financial era because it prioritizes being used over being hoarded.
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January 28, 2026

LIVE: BITGO IPO, HIP-3, KNTQ | 0xResearch

0xResearch

Crypto
Key Takeaways:
  1. Capital no longer distinguishes between AI stocks and rare metals. Investors treat these as a single risk-on bucket settled on-chain.
  2. Monitor Hyperliquid deployers. Identify protocols moving from passive yield to active market-making to capture the next commodity rotation.
  3. The next year will favor platforms providing access to diverse asset classes. Pure crypto protocols must adapt or lose mindshare to trade everything venues.
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January 26, 2026

Metals Alt Season, Catchup Trades, Bitcoin vs Gold, Crypto Is Dead

1000x Podcast

Crypto
Key Takeaways:
  1. The Macro Transition: Hard Asset Migration. As fiat currencies lose purchasing power, capital moves into finite assets, starting with Gold and Bitcoin before trickling down to Silver and Ethereum.
  2. The Tactical Edge: Buy the Laggard. Identify assets with strong fundamentals that have underperformed the market leader by more than 30%.
  3. The Bottom Line: The catchup trade is the most profitable strategy when the primary leaders are consolidating.
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January 24, 2026

Gold Sets the Bar, But Bitcoin Can Catch Up. Here’s How: Bits + Bips

Unchained

Crypto
Key Takeaways:
  1. The institutionalization of Bitcoin has temporarily sacrificed its digital gold status for liquidity, creating a massive opportunity for those who can stomach the volatility before the next decoupling.
  2. Monitor Japanese government bond yields as a leading indicator for global risk tolerance.
  3. Bitcoin is currently a liquidity sponge, not a bunker. Expect it to follow the Trump Put and tech earnings until its volatility profile mirrors a currency rather than a speculative stock.
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January 23, 2026

The Intersection of AI and Crypto: What Worked, What Didn’t, and What’s Next | Roundup

Bell Curve

Crypto
Key Takeaways:
  1. The market is moving from the "Compute Layer" to the "Agentic Layer." Owning the GPU is less valuable than owning the agent that controls the wallet.
  2. Build agent-first interfaces. Stop designing for human clicks and start structuring your data so an LLM can execute transactions on your behalf.
  3. The next 12 months belong to on-chain agents that handle treasury ops and commerce. The "decentralized GPU" narrative is dead. The "AI Agent with a bank account" narrative is just beginning.
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